1. Field
The present disclosure relates generally to graph analysis and, more specifically, to automatically extracting insightful nodes from graphs.
2. Description of the Related Art
Graphs are powerful data models for understanding systems in which relationships between entities are important. Examples include graphs characterizing relationships between documents, like semantic similarity between each document in a corpus, such as news articles published in a given decade, or between websites, or between scientific journal articles. Other examples include graphs characterizing relationships between other entities, like between companies, countries, or people, such as graphs relating exchanges there between or similarities there between.
Such graphs, however, can be difficult for humans to interpret, as the amount of information contained can massively exceed the capabilities of human cognition. Many typical applications have well in excess of 1,000 nodes and well in excess of 5,000 edges between those nodes. Lacking adequate tools for synthesizing knowledge from such data structures, many analysts fail to discover useful insights buried in graphs.